Management of overload condition for 5G or other next generation wireless network

ABSTRACT

A system that can detect a congested network node device that is overloaded due to number of user equipment (UE) devices connected to the network node device being determined to have exceeded a connection threshold; determine a second network node device that is available to establish connections with at least some of the UEs connected to the congested network node device; identify a third network node device that is transferring UE devices to the congested network node device to create additional connections; and transmit a cell individual offset (CIO) parameter and cell hysteresis offsets to the third network node device to reduce transferring UE devices to the congested network node device, and another CIO parameter and cell hysteresis offsets to the second network node device to increase establishment of the UE connection from the congested network node device.

RELATED APPLICATION

The subject patent application is a continuation of, and claims priorityto, U.S. patent application Ser. No. 16/536,092, filed Aug. 8, 2019, andentitled “MANAGEMENT OF OVERLOAD CONDITION FOR 5G OR OTHER NEXTGENERATION WIRELESS NETWORK,” the entirety of which application ishereby incorporated by reference herein.

TECHNICAL FIELD

This disclosure relates generally to management of overload condition ina wireless network. More specifically, facilitating management ofnetwork node devices that are overloaded, e.g., for 5th generation (5G)or other next generation wireless network.

BACKGROUND

5G wireless systems represent a next major phase of mobiletelecommunications standards beyond the current telecommunicationsstandards of 4^(th) generation (4G). In addition to faster peak Internetconnection speeds, 5G planning aims at higher capacity than current 4G,allowing a higher number of mobile broadband users per area unit, andallowing consumption of higher or unlimited data quantities. 5G researchand development also aims reduce congestion at network node devices(e.g., base stations). In 5G, a central controller can manage resourcesand performance of several network node devices. For example, networkcommunication devices (e.g., user equipment—UE) are distributed acrossnetwork and network node devices. Every time a UE device establishes aconnection to a network node device, it consumes resources. Theresources are limited and can be exhausted if large number of UE devicesare connecting to the network node device, thereby causing congestion oroverloading the network node device.

The above-described background relating to network node devicecongestion, is merely intended to provide a contextual overview of somecurrent issues, and is not intended to be exhaustive (e.g., althoughproblems and solution are directed to next generation networks such as5G, the solutions can be applied to 4G/long term evolution (LTE) and or5G LTE-new radio technologies). Other contextual information may becomefurther apparent upon review of the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the subject disclosureare described with reference to the following figures, wherein likereference numerals refer to like parts throughout the various viewsunless otherwise specified.

FIG. 1 illustrates an example wireless communication system in which anetwork node device and (UE) can implement various aspects andembodiments of the subject disclosure.

FIG. 2 illustrates an example schematic system block diagram ofintegrated access and backhaul links according to one or moreembodiments.

FIG. 3 illustrates an example of a wireless network in accordance withvarious aspects and embodiments described herein.

FIG. 4 illustrates a block diagram of an example, non-limiting systemthat facilitates management of network node devices that are overload.

FIG. 5 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 6 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 7 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 8 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 9 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 10 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein.

FIG. 11 illustrates an example block diagram of an example computeroperable to engage in a system architecture that facilitates securewireless communication according to one or more embodiments describedherein.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth toprovide a thorough understanding of various embodiments. One skilled inthe relevant art will recognize, however, that the techniques describedherein can be practiced without one or more of the specific details, orwith other methods, components, materials, etc. In other instances,well-known structures, materials, or operations are not shown ordescribed in detail to avoid obscuring certain aspects.

Reference throughout this specification to “one embodiment,” or “anembodiment,” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment. Thus, the appearances of the phrase “in oneembodiment,” “in one aspect,” or “in an embodiment,” in various placesthroughout this specification are not necessarily all referring to thesame embodiment. Furthermore, the particular features, structures, orcharacteristics may be combined in any suitable manner in one or moreembodiments.

As utilized herein, terms “component,” “system,” “interface,” and thelike are intended to refer to a computer-related entity, hardware,software (e.g., in execution), and/or firmware. For example, a componentcan be a processor, a process running on a processor, an object, anexecutable, a program, a storage device, and/or a computer. By way ofillustration, an application running on a server and the server can be acomponent. One or more components can reside within a process, and acomponent can be localized on one computer and/or distributed betweentwo or more computers.

Further, these components can execute from various machine-readablemedia having various data structures stored thereon. The components cancommunicate via local and/or remote processes such as in accordance witha signal having one or more data packets (e.g., data from one componentinteracting with another component in a local system, distributedsystem, and/or across a network, e.g., the Internet, a local areanetwork, a wide area network, etc. with other systems via the signal).

As another example, a component can be an apparatus with specificfunctionality provided by mechanical parts operated by electric orelectronic circuitry; the electric or electronic circuitry can beoperated by a software application or a firmware application executed byone or more processors; the one or more processors can be internal orexternal to the apparatus and can execute at least a part of thesoftware or firmware application. As yet another example, a componentcan be an apparatus that provides specific functionality throughelectronic components without mechanical parts; the electroniccomponents can include one or more processors therein to executesoftware and/or firmware that confer(s), at least in part, thefunctionality of the electronic components. In an aspect, a componentcan emulate an electronic component via a virtual machine, e.g., withina cloud computing system.

The words “exemplary” and/or “demonstrative” are used herein to meanserving as an example, instance, or illustration. For the avoidance ofdoubt, the subject matter disclosed herein is not limited by suchexamples. In addition, any aspect or design described herein as“exemplary” and/or “demonstrative” is not necessarily to be construed aspreferred or advantageous over other aspects or designs, nor is it meantto preclude equivalent exemplary structures and techniques known tothose of ordinary skill in the art. Furthermore, to the extent that theterms “includes,” “has,” “contains,” and other similar words are used ineither the detailed description or the claims, such terms are intendedto be inclusive—in a manner similar to the term “comprising” as an opentransition word—without precluding any additional or other elements.

As used herein, the term “infer” or “inference” refers generally to theprocess of reasoning about, or inferring states of, the system,environment, user, and/or intent from a set of observations as capturedvia events and/or data. Captured data and events can include user data,device data, environment data, data from sensors, sensor data,application data, implicit data, explicit data, etc. Inference can beemployed to identify a specific context or action, or can generate aprobability distribution over states of interest based on aconsideration of data and events, for example.

Inference can also refer to techniques employed for composinghigher-level events from a set of events and/or data. Such inferenceresults in the construction of new events or actions from a set ofobserved events and/or stored event data, whether the events arecorrelated in close temporal proximity, and whether the events and datacome from one or several event and data sources. Various classificationschemes and/or systems (e.g., support vector machines, neural networks,expert systems, Bayesian belief networks, fuzzy logic, and data fusionengines) can be employed in connection with performing automatic and/orinferred action in connection with the disclosed subject matter.

In addition, the disclosed subject matter can be implemented as amethod, apparatus, or article of manufacture using standard programmingand/or engineering techniques to produce software, firmware, hardware,or any combination thereof to control a computer to implement thedisclosed subject matter. The term “article of manufacture” as usedherein is intended to encompass a computer program accessible from anycomputer-readable device, machine-readable device, computer-readablecarrier, computer-readable media, or machine-readable media. Forexample, computer-readable media can include, but are not limited to, amagnetic storage device, e.g., hard disk; floppy disk; magneticstrip(s); an optical disk (e.g., compact disk (CD), a digital video disc(DVD), a Blu-ray Disc™ (BD)); a smart card; a flash memory device (e.g.,card, stick, key drive); and/or a virtual device that emulates a storagedevice and/or any of the above computer-readable media.

As an overview, various embodiments are described herein to facilitatemanagement of network node devices that are overload. For simplicity ofexplanation, the methods (or algorithms) are depicted and described as aseries of acts. It is to be understood and appreciated that the variousembodiments are not limited by the acts illustrated and/or by the orderof acts. For example, acts can occur in various orders and/orconcurrently, and with other acts not presented or described herein.Furthermore, not all illustrated acts may be required to implement themethods. In addition, the methods could alternatively be represented asa series of interrelated states via a state diagram or events.Additionally, the methods described hereafter are capable of beingstored on an article of manufacture (e.g., a machine-readable storagemedium) to facilitate transporting and transferring such methodologiesto computers. The term article of manufacture, as used herein, isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media, including a non-transitorymachine-readable storage medium.

It should be noted that although various aspects and embodiments havebeen described herein in the context of 5G, Universal MobileTelecommunications System (UMTS), and/or Long-Term Evolution (LTE), orother next generation networks, the disclosed aspects are not limited to5G, a UMTS implementation, and/or an LTE implementation as thetechniques can also be applied in 3G, 4G or LTE systems. For example,aspects or features of the disclosed embodiments can be exploited insubstantially any wireless communication technology. Such wirelesscommunication technologies can include UMTS, Code Division MultipleAccess (CDMA), Wi-Fi, Worldwide Interoperability for Microwave Access(WiMAX), General Packet Radio Service (GPRS), Enhanced GPRS, ThirdGeneration Partnership Project (3GPP), LTE, Third Generation PartnershipProject 2 (3GPP2) Ultra Mobile Broadband (UMB), High Speed Packet Access(HSPA), Evolved High Speed Packet Access (HSPA+), High-Speed DownlinkPacket Access (HSDPA), High-Speed Uplink Packet Access (HSUPA), Zigbee,or another IEEE 802.XX technology. Additionally, substantially allaspects disclosed herein can be exploited in legacy telecommunicationtechnologies.

Described herein are systems, methods, articles of manufacture, andother embodiments or implementations that can facilitate management of anetwork node device that is overloaded. Facilitating management of anetwork node device that is overloaded can be implemented in connectionwith any type of device with a connection to the communications network(e.g., a mobile handset, a computer, a handheld device, etc.) anyInternet of Things (IoT) device (e.g., toaster, coffee maker, blinds,music players, speakers, etc.), and/or any connected vehicles (cars,airplanes, space rockets, and/or other at least partially automatedvehicles (e.g., drones)). In some embodiments the non-limiting term userequipment (UE) is used. It can refer to any type of wireless device thatcommunicates with a radio network node in a cellular or mobilecommunication system. Examples of UE are target device, device to device(D2D) UE, machine type UE or UE capable of machine to machine (M2M)communication, PDA, Tablet, mobile terminals, smart phone, laptopembedded equipped (LEE), laptop mounted equipment (LME), USB dongles,etc. Note that the terms element, elements and antenna ports can beinterchangeably used but carry the same meaning in this disclosure. Theembodiments are applicable to single carrier as well as to multicarrier(MC) or carrier aggregation (CA) operation of the UE. The term carrieraggregation (CA) is also called (e.g., interchangeably called)“multi-carrier system”, “multi-cell operation”, “multi-carrieroperation”, “multi-carrier” transmission and/or reception.

In some embodiments the non-limiting term radio, network node device, orsimply network node is used. It can refer to any type of network nodethat serves UE is connected to other network nodes or network elementsor any radio node from where UE receives a signal. Examples of radionetwork nodes are Node B, base station (BS), multi-standard radio (MSR)node such as MSR BS, evolved Node B (eNB or eNodeB), next generationNode B (gNB or gNodeB), network controller, radio network controller(RNC), base station controller (BSC), relay, donor node controllingrelay, base transceiver station (BTS), access point (AP), transmissionpoints, transmission nodes, remote radio unit (RRU), remote radio head(RRH), nodes in distributed antenna system (DAS), relay device, networknode, node device, etc.

Cloud radio access networks (RAN) can enable the implementation ofconcepts such as software-defined network (SDN) and network functionvirtualization (NFV) in 5G networks. This disclosure can facilitate ageneric channel state information framework design for a 5G network.Certain embodiments of this disclosure can comprise an SDN controller(e.g., controller, central controller, or centralized unit) that cancontrol routing of traffic within the network and between the networkand traffic destinations. The SDN controller can be merged with the 5Gnetwork architecture to enable service deliveries via open applicationprogramming interfaces (“APIs”) and move the network core towards an allinternet protocol (“IP”), cloud based, and software driventelecommunications network. The SDN controller can work with or take theplace of policy and charging rules function (“PCRF”) network elements sothat policies such as quality of service and traffic management androuting can be synchronized and managed end to end.

In LTE systems, a central controller (e.g., a core network) managesresources and performance of several network node devices. For example,UE devices are distributed across network and network node devices(e.g., e/gNodeB, base stations, etc.). Every time a UE deviceestablishes a connection to a network node device (e.g. cell of anetwork node device), it consumes resources. The resources in this case,physical downlink control channel (PDCCH) control channel elements (CCE)are limited and can be exhausted if large number of UE devices attemptsconnecting to the network node. The resource exhaustion results in UEconnection establishment rejection (access failure) and throughputdegradation for the UE devices already connected to a congested cell.This can cause poor user experience for the cell phone users. Acongestion and high utilization of resources in a network node devicecan negatively impact all types of devices and users, including regularcustomers, high priority service devices and priority customers (e.g.,first responders).

According to some embodiments, a traffic offload management system isdescribed herein that can manage offloading of traffic (e.g., UEconnections) to reduce congestion at the overloaded/congested networknode device. In some embodiments, to improve the UE and network nodedevice performance (e.g., reduce high load on cells, reduce or removeestablishment rejections occurrence and improve throughput and userperformance) on overloaded network node device, the system moves trafficfrom overloaded network node device to other neighboring that are notoverloaded or have available capacity. In addition, the system canreduce or control incoming traffic from other neighboring network nodedevices until the congestion at the congested network node is reduced.In some embodiments, the system uses a combination of coordinatedparameter changes on detected overloaded network node device andneighboring network node devices to increase acceptance of traffic fromoverloaded network node device and reduce transferring traffic to theoverloaded network node device (e.g., reduce the number of UE beingtransferred to the already overloaded network node device). Theparameters are optimized as a group of network node devices rather thanone network node. The system can determine parameter settings for theoverloaded network node device and neighboring network node devicesbased on predicted performance of the affected network node devices(e.g., group of network node devices).

According an embodiment, a system can comprise a processor and a memorythat stores executable instructions that, when executed by theprocessor, facilitate performance of operations comprising detecting afirst network node device that is overloaded due to a number of a firstgroup of first network communication devices connected to the firstnetwork node device being determined to have exceeded a connectionthreshold. The system can further facilitate selecting a second networknode device comprising resources available to create first connectionswith at least some of the first group of first network communicationdevices connected to the first network node device. The system canfurther facilitate identifying a third network node device that istransferring a second group of second network communication devices,different than the first group of first network communication devices,to the first network node device to create second connections with thefirst network node device. The system can further facilitatetransmitting a first parameter to the third network node device tofacilitate a reduction in the transferring of the second group of secondnetwork communication devices to the first network node device, and asecond parameter to the second network node device to facilitateincrease in establishment of the first connections of the first group offirst network communication devices with the second network node device.

According to another embodiment, described herein is a method that cancomprise identifying, by a device comprising a processor, a firstnetwork node device that is overloaded based on a channel usage valuedetermined to be above a threshold due to first network communicationdevices connected to the first network node device. The method canfurther comprise determining, by the device, a second network nodedevice that is available to establish first connections with at leastsome of the first network communication devices connected to the firstnetwork node device. The method can further comprise identifying, by thedevice, a third network node device that is transferring second networkcommunication devices to the first network node device to create secondconnections with the first network node device. The method can furthercomprise facilitating, by the device, transmitting a first parameter tothe third network node device to facilitate a reduction in thetransferring of the second network communication devices to the firstnetwork node device, and facilitating, by the device, transmitting asecond parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices.

According to yet another embodiment, a device can comprise a processorand a memory that stores executable instructions that, when executed bythe processor, facilitate performance of operations comprising detectinga first network node device that is overloaded due to first networkcommunication devices connected to the first network node device beingdetermined to have exceeded a connection threshold. The device canfurther comprise determining a second network node device that isavailable to establish first connections with a group of the firstnetwork communication devices connected to the first network nodedevice. The device can further comprise identifying a third network nodedevice that is transferring second network communication devices to thefirst network node device to create additional connections with thefirst network node device. The device can further comprise transmittinga first parameter to the third network node device to facilitate areduction in the transferring of the second network communicationdevices to the first network node device, and a second parameter to thesecond network node device to facilitate increase in establishment ofthe first connections of the group of the first network communicationdevices.

These and other embodiments or implementations are described in moredetail below with reference to the drawings. Repetitive description oflike elements employed in the figures and other embodiments describedherein is omitted for sake of brevity.

FIG. 1 illustrates a non-limiting example of a wireless communicationsystem 100 in accordance with various aspects and embodiments of thesubject disclosure. In one or more embodiments, system 100 can compriseone or more user equipment UEs 102. The non-limiting term user equipmentcan refer to any type of device that can communicate with a network nodein a cellular or mobile communication system. A UE can have one or moreantenna panels having vertical and horizontal elements. Examples of a UEcomprise a target device, device to device (D2D) UE, machine type UE orUE capable of machine to machine (M2M) communications, personal digitalassistant (PDA), tablet, mobile terminals, smart phone, laptop mountedequipment (LME), universal serial bus (USB) dongles enabled for mobilecommunications, a computer having mobile capabilities, a mobile devicesuch as cellular phone, a laptop having laptop embedded equipment (LEE,such as a mobile broadband adapter), a tablet computer having a mobilebroadband adapter, a wearable device, a virtual reality (VR) device, aheads-up display (HUD) device, a smart car, a machine-type communication(MTC) device, and the like. User equipment UE 102 can also comprise IOTdevices that communicate wirelessly.

In various embodiments, system 100 is or comprises a wirelesscommunication network serviced by one or more wireless communicationnetwork providers. In example embodiments, a UE 102 can becommunicatively coupled to the wireless communication network via anetwork node 104. The network node (e.g., network node device) cancommunicate with user equipment (UE), thus providing connectivitybetween the UE and the wider cellular network. The UE 102 can sendtransmission type recommendation data to the network node 104. Thetransmission type recommendation data can comprise a recommendation totransmit data via a closed loop MIMO mode and/or a rank-1 precoder mode.

A network node can have a cabinet and other protected enclosures, anantenna mast, and multiple antennas for performing various transmissionoperations (e.g., MIMO operations). Network nodes can serve severalcells, also called sectors, depending on the configuration and type ofantenna. In example embodiments, the UE 102 can send and/or receivecommunication data via a wireless link to the network node 104. Thedashed arrow lines from the network node 104 to the UE 102 representdownlink (DL) communications and the solid arrow lines from the UE 102to the network nodes 104 represents an uplink (UL) communication.

System 100 can further include one or more communication serviceprovider networks 106 that facilitate providing wireless communicationservices to various UEs, including UE 102, via the network node 104and/or various additional network devices (not shown) included in theone or more communication service provider networks 106. The one or morecommunication service provider networks 106 can include various types ofdisparate networks, including but not limited to: cellular networks,femto networks, picocell networks, microcell networks, internet protocol(IP) networks Wi-Fi service networks, broadband service network,enterprise networks, cloud based networks, millimeter wave networks andthe like. For example, in at least one implementation, system 100 can beor include a large scale wireless communication network that spansvarious geographic areas. According to this implementation, the one ormore communication service provider networks 106 can be or include thewireless communication network and/or various additional devices andcomponents of the wireless communication network (e.g., additionalnetwork devices and cell, additional UEs, network server devices, etc.).The network node 104 can be connected to the one or more communicationservice provider networks 106 via one or more backhaul links 108. Forexample, the one or more backhaul links 108 can comprise wired linkcomponents, such as a T1/E1 phone line, a digital subscriber line (DSL)(e.g., either synchronous or asynchronous), an asymmetric DSL (ADSL), anoptical fiber backbone, a coaxial cable, and the like. The one or morebackhaul links 108 can also include wireless link components, such asbut not limited to, line-of-sight (LOS) or non-LOS links which caninclude terrestrial air-interfaces or deep space links (e.g., satellitecommunication links for navigation).

Wireless communication system 100 can employ various cellular systems,technologies, and modulation modes to facilitate wireless radiocommunications between devices (e.g., the UE 102 and the network node104). While example embodiments might be described for 5G new radio (NR)systems, the embodiments can be applicable to any radio accesstechnology (RAT) or multi-RAT system where the UE operates usingmultiple carriers e.g. LTE FDD/TDD, GSM/GERAN, CDMA2000 etc.

For example, system 100 can operate in accordance with global system formobile communications (GSM), universal mobile telecommunications service(UMTS), long term evolution (LTE), LTE frequency division duplexing (LTEFDD, LTE time division duplexing (TDD), high speed packet access (HSPA),code division multiple access (CDMA), wideband CDMA (WCMDA), CDMA2000,time division multiple access (TDMA), frequency division multiple access(FDMA), multi-carrier code division multiple access (MC-CDMA),single-carrier code division multiple access (SC-CDMA), single-carrierFDMA (SC-FDMA), orthogonal frequency division multiplexing (OFDM),discrete Fourier transform spread OFDM (DFT-spread OFDM) single carrierFDMA (SC-FDMA), Filter bank based multi-carrier (FBMC), zero tailDFT-spread-OFDM (ZT DFT-s-OFDM), generalized frequency divisionmultiplexing (GFDM), fixed mobile convergence (FMC), universal fixedmobile convergence (UFMC), unique word OFDM (UW-OFDM), unique wordDFT-spread OFDM (UW DFT-Spread-OFDM), cyclic prefix OFDM CP-OFDM,resource-block-filtered OFDM, Wi Fi, WLAN, WiMax, and the like. However,various features and functionalities of system 100 are particularlydescribed wherein the devices (e.g., the UEs 102 and the network device104) of system 100 are configured to communicate wireless signals usingone or more multi carrier modulation schemes, wherein data symbols canbe transmitted simultaneously over multiple frequency subcarriers (e.g.,OFDM, CP-OFDM, DFT-spread OFMD, UFMC, FMBC, etc.). The embodiments areapplicable to single carrier as well as to multicarrier (MC) or carrieraggregation (CA) operation of the UE. The term carrier aggregation (CA)is also called (e.g. interchangeably called) “multi-carrier system”,“multi-cell operation”, “multi-carrier operation”, “multi-carrier”transmission and/or reception. Note that some embodiments are alsoapplicable for Multi RAB (radio bearers) on some carriers (that is dataplus speech is simultaneously scheduled).

In various embodiments, system 100 can be configured to provide andemploy 5G wireless networking features and functionalities. 5G wirelesscommunication networks are expected to fulfill the demand ofexponentially increasing data traffic and to allow people and machinesto enjoy gigabit data rates with virtually zero latency. Compared to 4G,5G supports more diverse traffic scenarios. For example, in addition tothe various types of data communication between conventional UEs (e.g.,phones, smartphones, tablets, PCs, televisions, Internet enabledtelevisions, etc.) supported by 4G networks, 5G networks can be employedto support data communication between smart cars in association withdriverless car environments, as well as machine type communications(MTCs). Considering the drastic different communication needs of thesedifferent traffic scenarios, the ability to dynamically configurewaveform parameters based on traffic scenarios while retaining thebenefits of multi carrier modulation schemes (e.g., OFDM and relatedschemes) can provide a significant contribution to the highspeed/capacity and low latency demands of 5G networks. With waveformsthat split the bandwidth into several sub-bands, different types ofservices can be accommodated in different sub-bands with the mostsuitable waveform and numerology, leading to an improved spectrumutilization for 5G networks.

To meet the demand for data centric applications, features of proposed5G networks may comprise: increased peak bit rate (e.g., 20 Gbps),larger data volume per unit area (e.g., high system spectralefficiency—for example about 3.5 times that of spectral efficiency oflong term evolution (LTE) systems), high capacity that allows moredevice connectivity both concurrently and instantaneously, lowerbattery/power consumption (which reduces energy and consumption costs),better connectivity regardless of the geographic region in which a useris located, a larger numbers of devices, lower infrastructuraldevelopment costs, and higher reliability of the communications. Thus,5G networks may allow for: data rates of several tens of megabits persecond should be supported for tens of thousands of users, 1 gigabit persecond to be offered simultaneously to tens of workers on the sameoffice floor, for example; several hundreds of thousands of simultaneousconnections to be supported for massive sensor deployments; improvedcoverage, enhanced signaling efficiency; reduced latency compared toLTE.

The upcoming 5G access network may utilize higher frequencies (e.g., >6GHz) to aid in increasing capacity. Currently, much of the millimeterwave (mmWave) spectrum, the band of spectrum between 30 GHz and 300 GHzis underutilized. The millimeter waves have shorter wavelengths thatrange from 10 millimeters to 1 millimeter, and these mmWave signalsexperience severe path loss, penetration loss, and fading. However, theshorter wavelength at mmWave frequencies also allows more antennas to bepacked in the same physical dimension, which allows for large-scalespatial multiplexing and highly directional beamforming.

Performance can be improved if both the transmitter and the receiver areequipped with multiple antennas. Multi-antenna techniques cansignificantly increase the data rates and reliability of a wirelesscommunication system. The use of multiple input multiple output (MIMO)techniques, which was introduced in the third-generation partnershipproject (3GPP) and has been in use (including with LTE), is amulti-antenna technique that can improve the spectral efficiency oftransmissions, thereby significantly boosting the overall data carryingcapacity of wireless systems. The use of multiple-input multiple-output(MIMO) techniques can improve mmWave communications, and has been widelyrecognized a potentially important component for access networksoperating in higher frequencies. MIMO can be used for achievingdiversity gain, spatial multiplexing gain and beamforming gain. Forthese reasons, MIMO systems are an important part of the 3rd and 4thgeneration wireless systems, and are planned for use in 5G systems.

Referring now to FIG. 2 , illustrated is an example schematic systemblock diagram of integrated access and backhaul links according to oneor more embodiments. For example, the network 200, as represented inFIG. 2 with integrated access and backhaul links, can allow a relay nodeto multiplex access and backhaul links in time, frequency, and/or space(e.g. beam-based operation). Thus, FIG. 2 illustrates a generic IABset-up comprising a core network 202, a centralized unit 204, a donordistributed unit 206, a relay distributed unit 208, and UEs 1021, 1022,1023. The donor distributed unit 206 (e.g., access point) can have awired backhaul with a protocol stack and can relay the user traffic forthe UEs 1021, 1022, 1023 across the IAB and backhaul link. Then therelay distributed unit 208 can take the backhaul link and convert itinto different strains for the connected UEs 1021, 1022, 1023. AlthoughFIG. 2 depicts a single hop (e.g., over the air), it should be notedthat multiple backhaul hops can occur in other embodiments.

The relays can have the same type of distributed unit structure that thegNode B has. For 5G, the protocol stack can be split, where some of thestack is centralized. For example, the PDCP layer and above can be atthe centralized unit 204, but in a real time application part of theprotocol stack, the radio link control (RLC), the medium access control(MAC), and the physical layer PHY can be co-located with the basestation wherein the system can comprise an F1 interface. In order to addrelaying, the F1 interface can be wireless so that the same structure ofthe donor distributed unit 206 can be kept.

Referring now to FIG. 3 , illustrated is an example of a wirelessnetwork (e.g., 5G LTE-NR or other next generation wireless network) 300in accordance with various aspects and embodiments described herein. Thewireless network 300 can comprise several network node devices (e.g.,e/gNodeB, base station, etc.) 302-312. All the network node devices arecommunicatively connected to a core network 320 through the SDNcontroller. In some embodiments, one or devices of the core network 320,including the SDN controller 322 can monitor load value and/orcongestion status of all the network node devices 302-312 and takeappropriate action to reduce the load. In some embodiments, the networknode device 302 is illustrated as being overloaded (e.g., acongested/problem device, wherein number of connected UEs has reached athreshold, for example 70% of node device capacity). The network nodedevice can be considered overloaded for example, but not limited to, ifthe number of UE connected is over a threshold or based on performanceindicators indicating that utilization of a physical downlink controlchannel, control channel elements of a network node devices has reachedabove a pre-defined threshold (e.g., over 70%). The network device 304is considered as an outgoing network node device (e.g., a second networknode device) that is available to take some of the UE connection fromthe congested network node device 302. The SDN controller can conductmeasurements to determine if the outgoing network node device 304 isavailable to receive additional connection without reaching its ownoverload connection threshold. Also, the SDN controller 322 can analyzegeo-location relationships with the problem device 302 before selectingthe outgoing device to transfer some of the UE connection from theproblem device 302. The transferring at least some of the UE connectionsis illustrated as 354. The network devices 306 and 308 are considered toincoming devices (e.g., third network node devices). The incomingdevices 306 and 308 increase the load capacity of the congested device302 by transferring additional UEs to connect with the congested device302. The incoming connections are illustrated as 350 and 352. Inaccordance with some embodiments, the outgoing devices 304 and 306, andthe incoming device 304 are located with a geographical locationillustrated by 360. In some embodiments, the SDN controller 322 mayselect one or more incoming devices located within the geographicalboundary 360. The identity and priority of incoming and outgoing networkdevices can also be identified using handover neighbor relations(configuration management database) and historical handover counts(performance management database) between network devices. Other methodsof identity and priority of incoming and outgoing network devices can beused. If there are no network devices located within the geographicallocation 360, then the SDN controller can select other devices 310and/or 312 as incoming devices for receiving UE connections from theproblem devices.

FIG. 4 illustrates a block diagram of an example, non-limiting system400 that facilitates management of network node devices that areoverload in accordance with one or more embodiments described herein.According to some embodiments, the system 400 can comprise a congestionanalytics component 402. In some embodiments, the congestion analyticscomponent 402 can also include or otherwise be associated with a memory404, a processor 406 that executes computer executable components storedin a memory 404. The congestion analytics component 402 can furtherinclude a system bus 408 that can couple various components including,but not limited to, a detecting component 410, an offloading component412, a reduction component 414 and a transmitting component 416.

Aspects of systems (e.g., the congestion analytics component 402 and thelike), apparatuses, or processes explained in this disclosure canconstitute machine-executable component(s) embodied within machine(s),e.g., embodied in one or more computer readable mediums (or media)associated with one or more machines. Such component(s), when executedby the one or more machines, e.g., computer(s), computing device(s),virtual machine(s), etc. can cause the machine(s) to perform theoperations described.

It should be appreciated that the embodiments of the subject disclosuredepicted in various figures disclosed herein are for illustration only,and as such, the architecture of such embodiments are not limited to thesystems, devices, and/or components depicted therein. For example, insome embodiments, the congestion analytics component 402 can comprisevarious computer and/or computing-based elements described herein withreference to operating environment 1100 and FIG. 11 . In severalembodiments, such computer and/or computing-based elements can be usedin connection with implementing one or more of the systems, devices,and/or components shown and described in connection with FIG. 4 or otherfigures disclosed herein.

According to several embodiments, the memory 404 can store one or morecomputer and/or machine readable, writable, and/or executable componentsand/or instructions that, when executed by processor 406, can facilitateperformance of operations defined by the executable component(s) and/orinstruction(s). For example, the memory 404 can store computer and/ormachine readable, writable, and/or executable components and/orinstructions that, when executed by the processor 406, can facilitateexecution of the various functions described herein relating to thedetecting component 410, the offloading component 412, the reductioncomponent 414 and the transmitting component 416.

In several embodiments, the memory 404 can comprise volatile memory(e.g., random access memory (RAM), static RAM (SRAM), dynamic RAM(DRAM), etc.) and/or non-volatile memory (e.g., read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), etc.) that can employone or more memory architectures. Further examples of memory 404 aredescribed below with reference to system memory 1106 and FIG. 11 . Suchexamples of memory 404 can be employed to implement any embodiments ofthe subject disclosure.

According to some embodiments, the processor 406 can comprise one ormore types of processors and/or electronic circuitry that can implementone or more computer and/or machine readable, writable, and/orexecutable components and/or instructions that can be stored on thememory 404. For example, the processor 406 can perform variousoperations that can be specified by such computer and/or machinereadable, writable, and/or executable components and/or instructionsincluding, but not limited to, logic, control, input/output (I/O),arithmetic, and/or the like. In some embodiments, processor 406 cancomprise one or more central processing unit, multi-core processor,microprocessor, dual microprocessors, microcontroller, System on a Chip(SOC), array processor, vector processor, and/or another type ofprocessor.

In some embodiments, the processor 406, the memory 404, the detectingcomponent 410, the offloading component 412, the reduction component 414and the transmitting component 416 can be communicatively, electrically,and/or operatively coupled to one another via the system bus 408 toperform functions of the congestion analytics component 402, and/or anycomponents coupled therewith. In several embodiments, the system bus 408can comprise one or more memory bus, memory controller, peripheral bus,external bus, local bus, and/or another type of bus that can employvarious bus architectures.

In several embodiments, the congestion analytics component 402 cancomprise one or more computer and/or machine readable, writable, and/orexecutable components and/or instructions that, when executed by theprocessor 406, can facilitate performance of operations defined by suchcomponent(s) and/or instruction(s). Further, in numerous embodiments,any component associated with the congestion analytics component 402, asdescribed herein with or without reference to the various figures of thesubject disclosure, can comprise one or more computer and/or machinereadable, writable, and/or executable components and/or instructionsthat, when executed by the processor 406, can facilitate performance ofoperations defined by such component(s) and/or instruction(s). Forexample, the detecting component 410, and/or any other componentsassociated with the congestion analytics component 402 (e.g.,communicatively, electronically, and/or operatively coupled with and/oremployed by Congestion analytics component 402), can comprise suchcomputer and/or machine readable, writable, and/or executablecomponent(s) and/or instruction(s). Consequently, according to numerousembodiments, the congestion analytics component 402 and/or anycomponents associated therewith, can employ the processor 406 to executesuch computer and/or machine readable, writable, and/or executablecomponent(s) and/or instruction(s) to facilitate performance of one ormore operations described herein with reference to the congestionanalytics component 402 and/or any such components associated therewith.

In some embodiments, the congestion analytics component 402 canfacilitate performance of operations related to and/or executed by thecomponents of congestion analytics component 402, for example, theprocessor 406, the memory 404, the detecting component 410, theoffloading component 412, the reduction component 414 and thetransmitting component 416. For example, as described in detail below,the congestion analytics component 402 can facilitate: detecting (e.g.,by the detecting component 410) a first network node device that isoverloaded due to a number of a first group of first networkcommunication devices connected to the first network node device beingdetermined to have exceeded a connection threshold; selecting (e.g., bythe offloading component 412) a second network node device comprisingresources available to create first connections with at least some ofthe first group of first network communication devices connected to thefirst network node device; identifying (e.g., by the reduction component414) a third network node device that is transferring a second group ofsecond network communication devices, different than the first group offirst network communication devices, to the first network node device tocreate second connections with the first network node device; andtransmitting (e.g., by the transmitting component 416) a first parameterto the third network node device to facilitate a reduction in thetransferring of the second group of second network communication devicesto the first network node device, and a second parameter to the secondnetwork node device to facilitate increase in establishment of the firstconnections of the first group of first network communication deviceswith the second network node device.

In some embodiments, the detecting component 410, can comprise one ormore processors, memory, and electrical circuitry. The detectingcomponent 410 detects at least one of the network node devices that isoverloaded. For example, a first network node (e.g., congested device302) is overloaded due to number of first network communication devices(e.g., UE devices or mobile handsets) connected to it and the system(e.g., congestion analytics component 402) has determined that totalnumber of UE devices connected to it has exceeded a connectionthreshold. In some embodiments, the overload condition is identifiedwhen the total number connections are using up resources over athreshold (e.g., 70% or more). In another embodiment, the overloadcondition is identified if number connections being rejected is over athreshold.

In some embodiments, the detecting component 410 may utilize, forexample a detection mechanism, additional components (not shown) to finda congested network node device (the network node device 302 or cell ofthe network node device 302 that is overloaded) condition. A networknode device may comprise one or more cells. Each cell may acceptconnection from UE. When network node device is considered congested, itmay be due on of the cell being congested. Therefore, when referencingan overloaded cell, in some embodiments, it is considered that thenetwork node device is congested or overloaded. In some embodiments, theoverloaded cell may implement techniques described herein for cell tocell transfer to reduce the congestion. The detection may be based oncell level performance, but not limited to, indicators measuring PDCCHCCE utilization. (or other selected by user cell load utilizationmetric). The detection mechanism monitors PDCCH CCE utilization (orother utilization or performance measures) of the cells in the network.As soon as the utilization at any cell reaches level above predefined byuser threshold—for example 70%—such cell is classified as the problemcell (cell with overload condition). The detection mechanism informs andpasses the name (or identity) of the overloaded cell and time of theoverload conditions to a problem solution analytics (PSA) module havingalgorithms executed by the processor 310, the offloading component 412,the reduction component 414 and the transmitting component 416 forfurther processing to reduce congestion.

In some embodiments, once an overloaded cell has been identified ordetected, the PSA module can retrieve the neighbor relation list (e.g.,list of network node devices operating within a geographical location)of the overloaded network node device (e.g., also referred to a “cell”).For each neighbor cell and overloaded cell, the performance metrics areretrieved such as, but not limited to, neighbor cell's utilization(e.g., PDCCH CCE utilization), cell throughput, accessibility. For eachneighbor relation with overloaded cell the number of mobility handover(HO) occurrences between overloaded cell and neighbor cell (e.g., inincoming and outgoing HO count). The performance metrics are retrievedfor the time period which correspond to the time of the overloadconditions and passed by the detection component 412.

In some embodiments, idle and active mode parameters and settings areretrieved for overloaded cell (e.g., a1a2searchThreshold, referencesignal received power (RSRP) or reference signal received quality(RSRQ), a3offset, a3hysteresis), and each neighbor relation link(CIO—cell individual offset, e.g., qOffsetCellEUtran). The parametersare retrieved for the time when overload conditions at identifiedoverloaded cell occurred.

The PSA module can retrieve geo-located RF measurements within apre-defined distance range from the overloaded cell. These measurementsare provided by any measurement reporting system, for example, but notlimited to Carrier IQ, Arieso Viavi. The measurement reporting systemcan measure and store RSRP or RSRQ RF measurements with geographicallocations of these measurements grouped into geographical area rasterbins (i.e. using MGRS—Military Grid Reference System). The geo-locatedRF data comprises, for example: a geo-BIN identity, a measured cell ID,an averaged RSRQ (or RSRP) corresponding to a cell in a geo-BIN, and anumber of measured instances of the RSRQ (or RSRP) in a geo-BIN and fora cell_ID. In some embodiments, a single geo-BIN can comprise at leastone record where a record will contain information for either theoverloaded cell or any cell from the neighbor list of the overloadedcell.

In some embodiments, the offloading component 412, can comprise one ormore processors, memory, and electrical circuitry. The offloadingcomponent 412, selects a second network node device (e.g., outgoingnetwork node device) comprising resources available to create firstconnections with at least some of the first network communicationdevices connected to the first network node device (e.g., the problemnetwork node device). According to some embodiments, upon retrieval ofmeasurements and parameters, the PSA can select one or more outgoingneighboring cells which have the highest traffic offload opportunityfrom the overloaded cell and available. The availability can be based oncell utilization, (e.g., PDCCH CCE utilization, is below definedthreshold—for example 60%) and/or cell throughput is above definedthreshold (e.g., above 1 Mbps). This verification determines whichneighboring cells can be used to shift traffic (e.g., offload) from theoverloaded cell.

In some embodiments, the reduction component 414, can comprise one ormore processors, memory, and electrical circuitry. The reductioncomponent 414, identifies a third network node device (e.g., incomingnetwork node device) that is transferring a second group of secondnetwork communication devices (e.g., inflow of UE connections),different than the first network communication devices, to the firstnetwork node device (e.g., the congested network node device) to createsecond connections with the first network node device. The PSA can alsoselect one or more incoming neighboring cells which have the highestnumber of HO incoming to the overloaded cell and cell utilization (forexample PDCCH CCE utilization) is below defined threshold—e.g., 60%. ThePSA identifies which neighboring cells can be used to reduce UE trafficinflow (e.g., UE connection coming/transferring in) to overloaded cell.

In some embodiments, the transmitting component 416, can comprise one ormore processors, memory, and electrical circuitry. The transmittingcomponent 416 transmits a first parameter (e.g., CIO) to the thirdnetwork node device to facilitate a reduction in the transferring of thesecond group of second network communication devices to the firstnetwork node device, and a second parameter to the second network nodedevice to facilitate increase in establishment of the first connectionsof the first network communication devices with the second network nodedevice.

For offloading traffic, the traffic offload will be achieved by changingactive and idle mode CIO parameters or cell hysteresis offset parameterson identified outgoing cell neighbor relation to make easy to reselectand hand over from the overloaded cell to outgoing cells (e.g., aparameter provided to the outgoing network node device (e.g., secondnetwork node device) to facilitate increase in establishment ofconnections of UE devices with the outgoing network node device (e.g.,second network node device). Each CIO parameter adjustment to encouragereselect and handover from an overloaded cell to a less-loaded cell willbe matched with reciprocal parameters to discourage handback from thesame less-loaded cell back towards the same overloaded cell. This willreduce probability of ping-pong and instability. Each set of active modeCIO parameter adjustments shall be matched with an equivalent set ofidle mode CIO parameter adjustments. This will match active and idlemode services areas, reduce probability of ping-pong and instability.

For reducing incoming traffic, the traffic can be reduced by changingactive and idle mode CIO parameters or cell hysteresis offset parameterson identified neighbor relation to make more difficult to reselect andhand over from incoming cell to overloaded cell (e.g., parametertransmitted/provided to the outgoing network node device to facilitate areduction in the transferring of the UE connections to the problemnetwork node device). The new CIO parameter value is changed by 2 dB tomake more difficult handovers to the overloaded cell. In someembodiments, the CIO value can be also derived by the calculating theoffload opportunity based on IQI data and by applying predictiveanalytics model described below. Each CIO parameter adjustment todiscourage reselect and handover from a less-loaded cell to anoverloaded cell will be matched with reciprocal parameters to encouragehandback from the overloaded cell back towards the less-loaded cell.This will reduce probability of ping-pong and instability. Each set ofactive mode CIO parameter adjustments shall be matched with anequivalent set of idle mode CIO parameter adjustments. This will matchactive and idle mode services areas, reduce probability of ping-pong andinstability.

In some embodiments, an offloading opportunity can be calculated foreach outgoing network node device using geo-located RF information. Theoffload opportunity is a total number of measured instances of the RSRQ(or RSRP) from geo-located RF data that qualify for a handover from theoverloaded cell to outgoing neighboring cell. The qualification criteriais based on parameters which determine inter-cell handover condition,for example for A3event based HO: a1a2searchThreshold(RSRP or RSRQ),a3offset, a3hysteresis, Cell Individual Offset (CIO), qOffsetCellEUtran.For example, let the beginningOffload_Opportunity_ProblemCell_with_OutgoingCell_X=0. For every geo BINthat contains the overloaded cell measurements and signal level (RSRP orRSRQ) of the overloaded cell that is below a1a2searchThreshold, if RSRQ(or RSRP) of an Outgoing Cell_X in a geo BIN is greater than RSRP (orRSRQ) of the overloaded cell +a3offset+a3hysteresis-CIO, then increaseOffload_Opportunity_ProblemCell_with_OutgoingCell_X by number ofmeasured instances (of RSRP or RSRQ) of the overloaded cell. The offloadopportunity value will change when CIO parameter is changed on aneighbor relation pair (e.g., overloaded cell—outgoing cell). Byincreasing or decreasing CIO value, the offload opportunity for each CIOvalue we can determine what CIO value provides highest offloadopportunity for each neighbor relation.

In some embodiments, PSA can select the neighbor relations and their CIOparameters based on offload opportunity, predicted cell load andpredicted cell throughput. For example, a machine learning model forpredicting cell load (i.e. PDCCH CCE utilization) and cell throughputcan be used determine the predicted cell load and predicted cellthroughput. The model can be trained based on historical data where theinput of the model (e.g., features) are measures which are correlatedwith cell load and cell throughput. The close correlation of thefeatures (e.g., number of users in a cell (Uc), PRB utilization (Pc),Bandwidth of the cell (B), Data Volume (Vc), number of handovers intocell (HOc)) with cell load (Lc) and cell throughput (Tc) can beobserved. In addition, the features of the model should be scalablebased on the offload opportunity change measured with current parametersconfiguration (e.g., baseline) and by the percentage of the change ofthe offload opportunity with new set of parameters.

For example, let current offload opportunity based on CIO=C parameterfrom the overloaded cell A to outgoing cell B is: OFc=0. Let new CIOparameter CIO=Y. Based on this CIO the new offload opportunity is OFn=Q.The percentage of change of the offload opportunity can be OF_p=100%*(OFn−OFc)/Ofn. Based on OF_p the input features of the predictive modelare adjusted for which new cell load and throughput can be predicted.Let Uc, Pc, Vc, HOc be current measured input features to the model andfor the current offload opportunity Ofc of the overloaded cell. Let Un,Pn, Vn, HOn are new input features for the overloaded cell which arecalculated as:

For Outgoing cells: Un=Uc+Uc*OF_p Pn=Pc+Pc*OF_p Vc=Vc+Vc*OF_pHOc=HOc+HOc*OF_p; and

For Problem cells: Un=Uc−Uc*OF_p Pn=Pc−Pc*OF_p Vc=Vc−Vc*OF_pHOc=HOc−HOc*OF_p.

Having Un, Pn, Vc, HOc applied as the input to the predictive model, thethroughput and cell load can be predicted for outgoing cells ofoverloaded cell. These predicted values will indicate what would be acell load and a cell throughput if new CIO=Y is applied on a relationbetween the overloaded cell and selected outgoing cell. Knowingpredicted cell load and throughput of the overloaded cell or outgoingcell for various CIO values will allow to select the best overloadedcell and outgoing cell relation with CIO value that will provide thebest improvement of cell load and throughput in the overloaded cell andleast cell load and throughput degradation in outgoing cell.

FIG. 5 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 500 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 500 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 5 .

Operation 502 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 504. Otherwise, take no actionand continue monitoring. Operation 504 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 506 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 508 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 510 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device).

FIG. 6 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 600 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 600 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 6 .

Operation 602 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 604. Otherwise, take no actionand continue monitoring. Operation 604 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 606 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 608 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 610 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device). Operation 612depicts facilitating, by the device, transmitting a third parameter tothe first network node device that facilitates identifying at least someof the second network communication devices that are able to participatein transfer of at least some of the first connections from the firstnetwork node device to the second network node device.

FIG. 7 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 700 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 700 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 7 .

Operation 702 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 704. Otherwise, take no actionand continue monitoring. Operation 704 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 706 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 708 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 710 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device). Operation 712depicts updating, by the device, the first parameter and the secondparameter based on estimating a network node device load value of thefirst network node device and the second network node device, and anetwork node device throughput value of the first network node deviceand the second network node device upon utilization of the firstparameter and the second parameter.

FIG. 8 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 800 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 800 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 8 .

Operation 802 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 804. Otherwise, take no actionand continue monitoring. Operation 804 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 806 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 808 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 810 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device). Operation 812depicts in response to the determining that the second network nodedevice is available to establish the first connections, transferring, bythe device, at least some of the first network communication devicesfrom the first network node device to the second network node device.

FIG. 9 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 900 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 900 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 9 .

Operation 902 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 904. Otherwise, take no actionand continue monitoring. Operation 904 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 906 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 908 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 910 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device). Operation 912depicts in response to the transferring of the at least some of thefirst network communication devices from the first network node device,analyzing, by the device, a load value of the first network node device.Operation 914 depicts based on a result of the analyzing, adjusting, bythe device, the first parameter and the second parameter to lower theload value of the first network node device.

FIG. 10 depicts a diagram of an example, non-limiting computerimplemented method that facilitates management of a network node devicethat is overloaded in accordance with one or more embodiments describedherein. In some examples, flow diagram 1000 can be implemented byoperating environment 1100 described below. It can be appreciated thatthe operations of flow diagram 1000 can be implemented in a differentorder than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1104) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 10.

Operation 1002 depicts determining if there is a congestion in thewireless network (e.g., at least one network node that is overloaded dueto a large number of UE connection). If there is a congestion in thewireless network, then perform operation 1004. Otherwise, take no actionand continue monitoring. Operation 1004 depicts identifying, by a devicecomprising a processor, a first network node device that is overloadedbased on a channel usage value determined to be above a threshold due tofirst network communication devices connected to the first network nodedevice (e.g., identifying a problem e/gNodeB or a network node device,congested device, having overload conditions). Operation 1006 depictsdetermining, by the device, a second network node device that isavailable to establish first connections with at least some of the firstnetwork communication devices connected to the first network node device(e.g., finding at least one available network node device or e/gNodeB,donor device, for shifting some of the connections from the congesteddevice). Operation 1008 depicts identifying, by the device, a thirdnetwork node device that is transferring second network communicationdevices to the first network node device to create second connectionswith the first network node device (e.g., identify neighboringe/gNodeBs, incoming device(s), that are continuingrequesting/sending/adding new UE connections to the congested device).Operation 1010 depicts facilitating, by the device, transmitting a firstparameter to the third network node device to facilitate a reduction inthe transferring of the second network communication devices to thefirst network node device, and facilitating, by the device, transmittinga second parameter to the second network node device to facilitateincrease in establishment of the first connections with the firstnetwork communication devices (e.g., transmit parameters to the donornetwork node device or e/gNodeB, donor device, so that the donor devicecan accept more connections and transmit parameters, to the incomingdevice that is sending additional connections, requesting to reduce theamount of connections being sent to the problem device). Operation 1012depicts determining, by the device, a group of offloading parameters,wherein the group of offloading parameters comprises an estimated numberof the first network communication devices that are able to betransferred from the first network node device (e.g., an offloadingopportunity to estimate how many devices that should be offloaded priorto actually offloading the devices). In some embodiments, a problemsolution analytics may be used to calculate offload opportunity for eachoutgoing neighboring cell using geo-located RF information.

Referring now to FIG. 11 , illustrated is an example block diagram of anexample computer 1100 operable to engage in a system architecture thatfacilitates wireless communications according to one or more embodimentsdescribed herein. The computer 1100 can provide networking andcommunication capabilities between a wired or wireless communicationnetwork and a server and/or communication device.

In order to provide additional context for various embodiments describedherein, FIG. 11 and the following discussion are intended to provide abrief, general description of a suitable computing environment 1100 inwhich the various embodiments of the embodiment described herein can beimplemented. While the embodiments have been described above in thegeneral context of computer-executable instructions that can run on oneor more computers, those skilled in the art will recognize that theembodiments can be also implemented in combination with other programmodules and/or as a combination of hardware and software.

Generally, program modules include routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the methods can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, minicomputers, mainframe computers, Internet of Things (IoT)devices, distributed computing systems, as well as personal computers,hand-held computing devices, microprocessor-based or programmableconsumer electronics, and the like, each of which can be operativelycoupled to one or more associated devices.

The illustrated embodiments of the embodiments herein can be alsopracticed in distributed computing environments where certain tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules can be located in both local and remote memory storage devices.

Computing devices typically include a variety of media, which caninclude computer-readable storage media, machine-readable storage media,and/or communications media, which two terms are used herein differentlyfrom one another as follows. Computer-readable storage media ormachine-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media or machine-readablestorage media can be implemented in connection with any method ortechnology for storage of information such as computer-readable ormachine-readable instructions, program modules, structured data orunstructured data.

Computer-readable storage media can include, but are not limited to,random access memory (RAM), read only memory (ROM), electricallyerasable programmable read only memory (EEPROM), flash memory or othermemory technology, compact disk read only memory (CD-ROM), digitalversatile disk (DVD), Blu-ray disc (BD) or other optical disk storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, solid state drives or other solid statestorage devices, or other tangible and/or non-transitory media which canbe used to store desired information. In this regard, the terms“tangible” or “non-transitory” herein as applied to storage, memory orcomputer-readable media, are to be understood to exclude onlypropagating transitory signals per se as modifiers and do not relinquishrights to all standard storage, memory or computer-readable media thatare not only propagating transitory signals per se.

Computer-readable storage media can be accessed by one or more local orremote computing devices, e.g., via access requests, queries or otherdata retrieval protocols, for a variety of operations with respect tothe information stored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and includes any information deliveryor transport media. The term “modulated data signal” or signals refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in one or more signals. By wayof example, and not limitation, communication media include wired media,such as a wired network or direct-wired connection, and wireless mediasuch as acoustic, RF, infrared and other wireless media.

With reference again to FIG. 11 , the example environment 1100 forimplementing various embodiments of the aspects described hereinincludes a computer 1102, the computer 1102 including a processing unit1104, a system memory 1106 and a system bus 1108. The system bus 1108couples system components including, but not limited to, the systemmemory 1106 to the processing unit 1104. The processing unit 1104 can beany of various commercially available processors. Dual microprocessorsand other multi-processor architectures can also be employed as theprocessing unit 1104.

The system bus 1108 can be any of several types of bus structure thatcan further interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 1106includes ROM 1110 and RAM 1112. A basic input/output system (BIOS) canbe stored in a non-volatile memory such as ROM, erasable programmableread only memory (EPROM), EEPROM, which BIOS contains the basic routinesthat help to transfer information between elements within the computer1102, such as during startup. The RAM 1112 can also include a high-speedRAM such as static RAM for caching data.

The computer 1102 further includes an internal hard disk drive (HDD)1114 (e.g., EIDE, SATA), one or more external storage devices 1116(e.g., a magnetic floppy disk drive (FDD) 1116, a memory stick or flashdrive reader, a memory card reader, etc.) and an optical disk drive 1120(e.g., which can read or write from a CD-ROM disc, a DVD, a BD, etc.).While the internal HDD 1114 is illustrated as located within thecomputer 1102, the internal HDD 1114 can also be configured for externaluse in a suitable chassis (not shown). Additionally, while not shown inenvironment 1100, a solid state drive (SSD) could be used in additionto, or in place of, an HDD 1114. The HDD 1114, external storagedevice(s) 1116 and optical disk drive 1120 can be connected to thesystem bus 1108 by an HDD interface 1124, an external storage interface1126 and an optical drive interface 1128, respectively. The interface1124 for external drive implementations can include at least one or bothof Universal Serial Bus (USB) and Institute of Electrical andElectronics Engineers (IEEE) 1394 interface technologies. Other externaldrive connection technologies are within contemplation of theembodiments described herein.

The drives and their associated computer-readable storage media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 1102, the drives andstorage media accommodate the storage of any data in a suitable digitalformat. Although the description of computer-readable storage mediaabove refers to respective types of storage devices, it should beappreciated by those skilled in the art that other types of storagemedia which are readable by a computer, whether presently existing ordeveloped in the future, could also be used in the example operatingenvironment, and further, that any such storage media can containcomputer-executable instructions for performing the methods describedherein.

A number of program modules can be stored in the drives and RAM 1112,including an operating system 1130, one or more application programs1132, other program modules 1134 and program data 1136. All or portionsof the operating system, applications, modules, and/or data can also becached in the RAM 1112. The systems and methods described herein can beimplemented utilizing various commercially available operating systemsor combinations of operating systems.

Computer 1102 can optionally comprise emulation technologies. Forexample, a hypervisor (not shown) or other intermediary can emulate ahardware environment for operating system 1130, and the emulatedhardware can optionally be different from the hardware illustrated inFIG. 11 . In such an embodiment, operating system 1130 can comprise onevirtual machine (VM) of multiple VMs hosted at computer 1102.Furthermore, operating system 1130 can provide runtime environments,such as the Java runtime environment or the .NET framework, forapplications 1132. Runtime environments are consistent executionenvironments that allow applications 1132 to run on any operating systemthat includes the runtime environment. Similarly, operating system 1130can support containers, and applications 1132 can be in the form ofcontainers, which are lightweight, standalone, executable packages ofsoftware that include, e.g., code, runtime, system tools, systemlibraries and settings for an application.

Further, computer 1102 can be enable with a security module, such as atrusted processing module (TPM). For instance with a TPM, bootcomponents hash next in time boot components, and wait for a match ofresults to secured values, before loading a next boot component. Thisprocess can take place at any layer in the code execution stack ofcomputer 1102, e.g., applied at the application execution level or atthe operating system (OS) kernel level, thereby enabling security at anylevel of code execution.

A user can enter commands and information into the computer 1102 throughone or more wired/wireless input devices, e.g., a keyboard 1138, a touchscreen 1140, and a pointing device, such as a mouse 1142. Other inputdevices (not shown) can include a microphone, an infrared (IR) remotecontrol, a radio frequency (RF) remote control, or other remote control,a joystick, a virtual reality controller and/or virtual reality headset,a game pad, a stylus pen, an image input device, e.g., camera(s), agesture sensor input device, a vision movement sensor input device, anemotion or facial detection device, a biometric input device, e.g.,fingerprint or iris scanner, or the like. These and other input devicesare often connected to the processing unit 1104 through an input deviceinterface 1144 that can be coupled to the system bus 1108, but can beconnected by other interfaces, such as a parallel port, an IEEE 1394serial port, a game port, a USB port, an IR interface, a BLUETOOTH®interface, etc.

A monitor 1146 or other type of display device can be also connected tothe system bus 1108 via an interface, such as a video adapter 1148. Inaddition to the monitor 1146, a computer typically includes otherperipheral output devices (not shown), such as speakers, printers, etc.

The computer 1102 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 1150. The remotecomputer(s) 1150 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallyincludes many or all of the elements described relative to the computer1102, although, for purposes of brevity, only a memory/storage device1152 is illustrated. The logical connections depicted includewired/wireless connectivity to a local area network (LAN) 1154 and/orlarger networks, e.g., a wide area network (WAN) 1156. Such LAN and WANnetworking environments are commonplace in offices and companies, andfacilitate enterprise-wide computer networks, such as intranets, all ofwhich can connect to a global communications network, e.g., theInternet.

When used in a LAN networking environment, the computer 1102 can beconnected to the local network 1154 through a wired and/or wirelesscommunication network interface or adapter 1158. The adapter 1158 canfacilitate wired or wireless communication to the LAN 1154, which canalso include a wireless access point (AP) disposed thereon forcommunicating with the adapter 1158 in a wireless mode.

When used in a WAN networking environment, the computer 1102 can includea modem 1160 or can be connected to a communications server on the WAN1156 via other means for establishing communications over the WAN 1156,such as by way of the Internet. The modem 1160, which can be internal orexternal and a wired or wireless device, can be connected to the systembus 1108 via the input device interface 1144. In a networkedenvironment, program modules depicted relative to the computer 1102 orportions thereof, can be stored in the remote memory/storage device1152. It will be appreciated that the network connections shown areexample and other means of establishing a communications link betweenthe computers can be used.

When used in either a LAN or WAN networking environment, the computer1102 can access cloud storage systems or other network-based storagesystems in addition to, or in place of, external storage devices 1116 asdescribed above. Generally, a connection between the computer 1102 and acloud storage system can be established over a LAN 1154 or WAN 1156e.g., by the adapter 1158 or modem 1160, respectively. Upon connectingthe computer 1102 to an associated cloud storage system, the externalstorage interface 1126 can, with the aid of the adapter 1158 and/ormodem 1160, manage storage provided by the cloud storage system as itwould other types of external storage. For instance, the externalstorage interface 1126 can be configured to provide access to cloudstorage sources as if those sources were physically connected to thecomputer 1102.

The computer 1102 can be operable to communicate with any wirelessdevices or entities operatively disposed in wireless communication,e.g., a printer, scanner, desktop and/or portable computer, portabledata assistant, communications satellite, any piece of equipment orlocation associated with a wirelessly detectable tag (e.g., a kiosk,news stand, store shelf, etc.), and telephone. This can include WirelessFidelity (Wi-Fi) and BLUETOOTH® wireless technologies. Thus, thecommunication can be a predefined structure as with a conventionalnetwork or simply an ad hoc communication between at least two devices.

The above description of illustrated embodiments of the subjectdisclosure, including what is described in the Abstract, is not intendedto be exhaustive or to limit the disclosed embodiments to the preciseforms disclosed. While specific embodiments and examples are describedherein for illustrative purposes, various modifications are possiblethat are considered within the scope of such embodiments and examples,as those skilled in the relevant art can recognize.

In this regard, while the disclosed subject matter has been described inconnection with various embodiments and corresponding Figures, whereapplicable, it is to be understood that other similar embodiments can beused or modifications and additions can be made to the describedembodiments for performing the same, similar, alternative, or substitutefunction of the disclosed subject matter without deviating therefrom.Therefore, the disclosed subject matter should not be limited to anysingle embodiment described herein, but rather should be construed inbreadth and scope in accordance with the appended claims below.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor may also be implemented as acombination of computing processing units.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “selector,” “interface,” and the like are intendedto refer to a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration and not limitation, both anapplication running on a server and the server can be a component. Oneor more components may reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers. In addition, these componentscan execute from various computer readable media, device readablestorage devices, or machine readable media having various datastructures stored thereon. The components may communicate via localand/or remote processes such as in accordance with a signal having oneor more data packets (e.g., data from one component interacting withanother component in a local system, distributed system, and/or across anetwork such as the Internet with other systems via the signal). Asanother example, a component can be an apparatus with specificfunctionality provided by mechanical parts operated by electric orelectronic circuitry, which is operated by a software or firmwareapplication executed by a processor, wherein the processor can beinternal or external to the apparatus and executes at least a part ofthe software or firmware application. As yet another example, acomponent can be an apparatus that provides specific functionalitythrough electronic components without mechanical parts, the electroniccomponents can include a processor therein to execute software orfirmware that confers at least in part the functionality of theelectronic components.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form.

Moreover, terms like “user equipment (UE),” “mobile station,” “mobile,”subscriber station,” “subscriber equipment,” “access terminal,”“terminal,” “handset,” and similar terminology, refer to a wirelessdevice utilized by a subscriber or user of a wireless communicationservice to receive or convey data, control, voice, video, sound, gaming,or substantially any data-stream or signaling-stream. The foregoingterms are utilized interchangeably in the subject specification andrelated drawings. Likewise, the terms “access point (AP),” “basestation,” “NodeB,” “evolved Node B (eNodeB),” “home Node B (HNB),” “homeaccess point (HAP),” “cell device,” “sector,” “cell,” “relay device,”“node,” “point,” and the like, are utilized interchangeably in thesubject application, and refer to a wireless network component orappliance that serves and receives data, control, voice, video, sound,gaming, or substantially any data-stream or signaling-stream to and froma set of subscriber stations or provider enabled devices. Data andsignaling streams can include packetized or frame-based flows.

Additionally, the terms “core-network”, “core”, “core carrier network”,“carrier-side”, or similar terms can refer to components of atelecommunications network that typically provides some or all ofaggregation, authentication, call control and switching, charging,service invocation, or gateways. Aggregation can refer to the highestlevel of aggregation in a service provider network wherein the nextlevel in the hierarchy under the core nodes is the distribution networksand then the edge networks. UEs do not normally connect directly to thecore networks of a large service provider but can be routed to the coreby way of a switch or radio area network. Authentication can refer todeterminations regarding whether the user requesting a service from thetelecom network is authorized to do so within this network or not. Callcontrol and switching can refer determinations related to the futurecourse of a call stream across carrier equipment based on the callsignal processing. Charging can be related to the collation andprocessing of charging data generated by various network nodes. Twocommon types of charging mechanisms found in present day networks can beprepaid charging and postpaid charging. Service invocation can occurbased on some explicit action (e.g. call transfer) or implicitly (e.g.,call waiting). It is to be noted that service “execution” may or may notbe a core network functionality as third party network/nodes may takepart in actual service execution. A gateway can be present in the corenetwork to access other networks. Gateway functionality can be dependenton the type of the interface with another network.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“prosumer,” “agent,” and the like are employed interchangeablythroughout the subject specification, unless context warrants particulardistinction(s) among the terms. It should be appreciated that such termscan refer to human entities or automated components (e.g., supportedthrough artificial intelligence, as through a capacity to makeinferences based on complex mathematical formalisms), that can providesimulated vision, sound recognition and so forth.

Aspects, features, or advantages of the subject matter can be exploitedin substantially any, or any, wired, broadcast, wirelesstelecommunication, radio technology or network, or combinations thereof.Non-limiting examples of such technologies or networks include Geocasttechnology; broadcast technologies (e.g., sub-Hz, ELF, VLF, LF, MF, HF,VHF, UHF, SHF, THz broadcasts, etc.); Ethernet; X.25; powerline-typenetworking (e.g., PowerLine AV Ethernet, etc.); femto-cell technology;Wi-Fi; Worldwide Interoperability for Microwave Access (WiMAX); EnhancedGeneral Packet Radio Service (Enhanced GPRS); Third GenerationPartnership Project (3GPP or 3G) Long Term Evolution (LTE); 3GPPUniversal Mobile Telecommunications System (UMTS) or 3GPP UMTS; ThirdGeneration Partnership Project 2 (3GPP2) Ultra Mobile Broadband (UMB);High Speed Packet Access (HSPA); High Speed Downlink Packet Access(HSDPA); High Speed Uplink Packet Access (HSUPA); GSM Enhanced DataRates for GSM Evolution (EDGE) Radio Access Network (RAN) or GERAN; UMTSTerrestrial Radio Access Network (UTRAN); or LTE Advanced.

What has been described above includes examples of systems and methodsillustrative of the disclosed subject matter. It is, of course, notpossible to describe every combination of components or methods herein.One of ordinary skill in the art may recognize that many furthercombinations and permutations of the disclosure are possible.Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim.

While the various embodiments are susceptible to various modificationsand alternative constructions, certain illustrated implementationsthereof are shown in the drawings and have been described above indetail. It should be understood, however, that there is no intention tolimit the various embodiments to the specific forms disclosed, but onthe contrary, the intention is to cover all modifications, alternativeconstructions, and equivalents falling within the spirit and scope ofthe various embodiments.

In addition to the various implementations described herein, it is to beunderstood that other similar implementations can be used ormodifications and additions can be made to the describedimplementation(s) for performing the same or equivalent function of thecorresponding implementation(s) without deviating therefrom. Stillfurther, multiple processing chips or multiple devices can share theperformance of one or more functions described herein, and similarly,storage can be effected across a plurality of devices. Accordingly, thevarious embodiments are not to be limited to any single implementation,but rather are to be construed in breadth, spirit and scope inaccordance with the appended claims.

What is claimed is:
 1. A system, comprising: a processor; and a memorythat stores executable instructions that, when executed by theprocessor, facilitate performance of operations, comprising: determiningthat a first network node device satisfies an overload criterion relatedto a quantity of first network communication devices connected to thefirst network node device; identifying a second network node device thatis initiating handovers of second network communication devices,different than the first network communication devices, to the firstnetwork node device; transmitting a first parameter to the secondnetwork node device to facilitate a reduction in the handovers of thesecond network communication devices to the first network node device;selecting a third network node device that satisfies an availabilitythreshold; transmitting a second parameter to the third network nodedevice to facilitate a handover of the handovers of a networkcommunication device of the first network communication devices to thethird network node device; in response to the handover of the networkcommunication device to the third network node device, analyzing a loadvalue of the first network node device; and adjusting the firstparameter and the second parameter to modify the load value of the firstnetwork node device.
 2. The system of claim 1, wherein the determiningthat the first network node device satisfies the overload criterioncomprises utilizing a predictive model to predict a load value of thefirst network node device.
 3. The system of claim 1, wherein theselecting of the third network node device that satisfies theavailability threshold comprises utilizing a predictive model to predicta load value of the third network node device.
 4. The system of claim 1,wherein the operations further comprise: transmitting a third parameterto the first network node device, wherein the third parameter isutilized to facilitate the handover of the network communication deviceto the third network node device.
 5. The system of claim 1, wherein theoperations further comprise: in response to the determining that thefirst network node device satisfies the overload criterion, requestingchannel measurements from neighboring network node devices locatedwithin a geographical area.
 6. The system of claim 5, wherein therequesting of the channel measurements from the neighboring network nodedevices located within a geographical area comprises requesting thechannel measurements from the neighboring network node devices locatedwithin a geographical area and that satisfy a defined availabilitycriterion.
 7. A method, comprising: detecting, by a device comprising aprocessor, a first base station that is overloaded based on an overloadthreshold due to first user equipment connected to the first basestation; identifying, by the device, a second base station that istransferring second user equipment to the first base station;facilitating, by the device, transmitting a first parameter to thesecond base station to facilitate a reduction in the transferring of thesecond user equipment to the first base station; selecting, by thedevice, a third base station that satisfies an availability threshold;facilitating, by the device, transmitting a second parameter to thethird base station to facilitate transfer of a user equipment of thefirst user equipment to the second base station; in response to thetransfer of the user equipment to the third base station, analyzing, bythe device, a load of the first base station; and adjusting, by thedevice, the first parameter and the second parameter to modify the loadof the first base station.
 8. The method of claim 7, wherein thedetecting that the first base station is overloaded based on theoverload threshold comprises predicting, via a predictive model, a loadof the first base station.
 9. The method of claim 7, wherein theselecting of the third base station that satisfies the availabilitythreshold comprises utilizing a predictive model to predict a load valueof the third base station.
 10. The method of claim 7, furthercomprising: facilitating, by the device, transmitting a third parameterto the first base station, wherein the third parameter facilitates thetransfer of the user equipment to the third base station.
 11. The methodof claim 7, further comprising: in response to the detecting that thefirst base station is overloaded based on the overload threshold,requesting, by the device, channel measurements from neighboring basestations satisfying a defined qualification criterion.
 12. The method ofclaim 11, wherein the defined qualification criterion comprises athreshold base station throughput.
 13. The method of claim 11, whereinthe defined qualification criterion comprises a threshold base stationutilization.
 14. A non-transitory machine-readable medium, comprisingexecutable instructions that, when executed by a processor, facilitateperformance of operations, comprising: identifying a first access pointthat satisfies an overload criterion related to a quantity of firstmobile devices connected to the first access point being determined tohave exceeded a connection threshold; detecting a second access pointthat is transferring second mobile devices, different than the firstmobile devices, to the first access point; sending a first parameter tothe second access point to facilitate a reduction in the transferring ofthe second mobile devices to the first access point; selecting a thirdaccess point that satisfies an availability threshold; transmitting asecond parameter to the third access point to facilitate a transfer of amobile device of the first mobile devices to the second access point; inresponse to the transfer of the mobile device to the third access point,analyzing a load value of the first access point; and adjusting thefirst parameter and the second parameter to modify the load value of thefirst access point.
 15. The non-transitory machine-readable medium ofclaim 14, wherein the identifying the first access point that satisfiesthe overload criterion comprises predicting, via a predictive model, aload metric of the first access point.
 16. The non-transitorymachine-readable medium of claim 14, wherein the selecting of the thirdaccess point that satisfies the availability threshold comprisesutilizing a predictive model to predict a load value of the third accesspoint.
 17. The non-transitory machine-readable medium of claim 14,wherein the operations further comprise: transmitting a third parameterto the first access point, wherein the third parameter is utilized tofacilitate the transfer of the mobile device to the third access point.18. The non-transitory machine-readable medium of claim 14, wherein theoperations further comprise: in response to the detecting that the firstaccess point is overloaded based on the overload threshold, requestingchannel measurements from neighboring access points satisfying a definedcriterion.
 19. The non-transitory machine-readable medium of claim 18,wherein the criterion comprises a threshold access point throughput. 20.The non-transitory machine-readable medium of claim 18, wherein thecriterion comprises a threshold access point utilization.